Open Access
Issue |
E3S Web Conf.
Volume 511, 2024
International Conference on “Advanced Materials for Green Chemistry and Sustainable Environment” (AMGSE-2024)
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Article Number | 01012 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/e3sconf/202451101012 | |
Published online | 10 April 2024 |
- H. M. A. Farid and M. Riaz, “Single-valued neutrosophic dynamic aggregation information with time sequence preference for IoT technology in supply chain management,” Eng Appl Artif Intell, vol. 126, (2023). doi: 10.1016/j.engappai.2023.106940. [Google Scholar]
- R. Manivannan, “Research on IoT-based hybrid electrical vehicles energy management systems using machine learning-based algorithm,” Sustainable Computing: Informatics and Systems, vol. 41, (2024). doi: 10.1016/j.suscom.2023.100943. [CrossRef] [Google Scholar]
- M. S. Delgosha, N. Hajiheydari, and M. Talafidaryani, “Discovering IoT implications in business and management: A computational thematic analysis,” Technovation, vol. 118, (2022). doi: 10.1016/j.technovation.2021.102236. [CrossRef] [Google Scholar]
- S. H. Mekala, Z. Baig, A. Anwar, and S. Zeadally, “Cybersecurity for Industrial IoT (IIoT): Threats, countermeasures, challenges and future directions,” Comput Commun, vol. 208, pp. 294–320, (2023). doi: 10.1016/j.comcom.2023.06.020. [CrossRef] [Google Scholar]
- S. E. Bibri, “The IoT for smart sustainable cities of the future: An analytical framework for sensor-based big data applications for environmental sustainability,” Sustain Cities Soc, vol. 38, pp. 230–253, (2018). doi: 10.1016/j.scs.2017.12.034. [CrossRef] [Google Scholar]
- G. Yu, D. Lin, Y. Wang, M. Hu, V. Sugumaran, and J. Chen, “Digital Twin-enabled and Knowledge-driven decision support for tunnel electromechanical equipment maintenance,” Tunnelling and Underground Space Technology, vol. 140, (2023). doi: 10.1016/j.tust.2023.105318. [Google Scholar]
- A. Martikkala, B. Mayanti, P. Helo, A. Lobov, and I. F. Ituarte, “Smart textile waste collection system – Dynamic route optimization with IoT,” J Environ Manage, vol. 335, (2023). doi: 10.1016/j.jenvman.2023.117548. [CrossRef] [PubMed] [Google Scholar]
- M. M. Nair and A. K. Tyagi, “AI, IoT, blockchain, and cloud computing: The necessity of the future,” Distributed Computing to Blockchain: Architecture, Technology, and Applications, pp. 189–206, (2023). doi: 10.1016/B978-0-323-96146-2.00001-2. [Google Scholar]
- X. Qiu, H. Luo, G. Xu, R. Zhong, and G. Q. Huang, “Physical assets and service sharing for IoT-enabled Supply Hub in Industrial Park (SHIP),” Int J Prod Econ, vol. 159, pp. 4–15, (2015). doi: 10.1016/j.ijpe.2014.09.001. [CrossRef] [Google Scholar]
- “IoT-Enabled Predictive Maintenance for Sustainable Transportation Fleets Search | ScienceDirect.com.” Accessed: (2024). [Online]. Available: https://www.sciencedirect.com/search?qs=IoT-Enabled%20Predictive%20Maintenance%20for%20Sustainable%20Transportation%20Fleets [Google Scholar]
- M. Ammar et al., “Significant applications of smart materials and Internet of Things (IoT) in the automotive industry,” Mater Today Proc, vol. 68, pp. 1542–1549, (2022). doi: 10.1016/j.matpr.2022.07.180. [CrossRef] [Google Scholar]
- S. Singh, P. K. Sharma, B. Yoon, M. Shojafar, G. H. Cho, and I. H. Ra, “Convergence of blockchain and artificial intelligence in IoT network for the sustainable smart city,” Sustain Cities Soc, vol. 63, (2020). doi: 10.1016/j.scs.2020.102364. [CrossRef] [Google Scholar]
- A. Nazir et al., “Advancing IoT security: A systematic review of machine learning approaches for the detection of IoT botnets,” Journal of King Saud University Computer and Information Sciences, vol. 35, no. 10, (2023). doi: 10.1016/j.jksuci.2023.101820. [CrossRef] [Google Scholar]
- T. W. Chit, C. Toro, H. C. Lim, and R. Muthu, “Scalable Remote Cloud Data Center for Vessel Equipment Predictive Maintenance Service-as-aProduct (SaaP),” Procedia Comput Sci, vol. 225, pp. 2826–2834, (2023). doi: 10.1016/j.procs.2023.10.275. [CrossRef] [Google Scholar]
- G. Jelen, J. Babic, and V. Podobnik, “A multi-agent system for contextaware electric vehicle fleet routing: A step towards more sustainable urban operations,” J Clean Prod, vol. 374, (2022). doi: 10.1016/j.jclepro.2022.134047. [CrossRef] [Google Scholar]
- S. Nižetić, P. Šolić, D. López-de-Ipiña González-de-Artaza, and L. Patrono, “Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future,” J Clean Prod, vol. 274, (2020). doi: 10.1016/j.jclepro.2020.122877. [Google Scholar]
- D. Kumar, R. K. Singh, R. Mishra, and T. U. Daim, “Roadmap for integrating blockchain with Internet of Things (IoT) for sustainable and secured operations in logistics and supply chains: Decision making framework with case illustration,” Technol Forecast Soc Change, vol. 196, (2023). doi: 10.1016/j.techfore.2023.122837. [CrossRef] [Google Scholar]
- P. H. Brunheroto, A. L. G. Pepino, F. Deschamps, and E. de Freitas Rocha Loures, “Data analytics in fleet operations: A systematic literature review and workflow proposal,” Procedia CIRP, vol. 107, pp. 1192–1197, (2022). doi: 10.1016/j.procir.2022.05.130. [CrossRef] [Google Scholar]
- R. Dintén, S. García, and M. Zorrilla, “Fleet management systems in Logistics 4.0 era: a real time distributed and scalable architectural proposal,” Procedia Comput Sci, vol. 217, pp. 806–815, (2022). doi: 10.1016/j.procs.2022.12.277. [Google Scholar]
- H. Alqahtani and G. Kumar, “Machine learning for enhancing transportation security: A comprehensive analysis of electric and flying vehicle systems,” Eng Appl Artif Intell, vol. 129, (2024). doi: 10.1016/j.engappai.2023.107667. [CrossRef] [Google Scholar]
- M. V. Corazza, A. Toni, and D. Vasari, “What Bus Operators Want: Emissions Mitigation and Water Management to Maintain Cleaner Fleets in Europe,” Transportation Research Procedia, vol. 72, pp. 836–843, (2023). doi: 10.1016/j.trpro.2023.11.475. [CrossRef] [Google Scholar]
- V. Pachouri, R. Singh, A. Gehlot, S. Pandey, S. Vaseem Akram, and M. Abbas, “Empowering sustainability in the built environment: A technological Lens on industry 4.0 Enablers,” Technol Soc, vol. 76, Mar. (2024). doi: 10.1016/j.techsoc.2023.102427. [CrossRef] [Google Scholar]
- T. D. Mastos et al., “Industry 4.0 sustainable supply chains: An application of an IoT enabled scrap metal management solution,” J Clean Prod, vol. 269, (2020). doi: 10.1016/j.jclepro.2020.122377. [CrossRef] [Google Scholar]
- A. Jahid, M. H. Alsharif, and T. J. Hall, “The convergence of blockchain, IoT and 6G: Potential, opportunities, challenges and research roadmap,” Journal of Network and Computer Applications, vol. 217, (2023). doi: 10.1016/j.jnca.2023.103677. [CrossRef] [Google Scholar]
- A. Toni, M. V. Corazza, and D. Vasari, “Improving the environmental performance of bus fleets in Europe,” Transportation Research Procedia, vol. 69, pp. 147–154, (2023). doi: 10.1016/j.trpro.2023.02.156. [CrossRef] [Google Scholar]
- Md.Z. ul Haq, H. Sood, and R. Kumar, “Effect of using plastic waste on mechanical properties of fly ash based geopolymer concrete,” Mater Today Proc, (2022). [Google Scholar]
- A. Kumar, N. Mathur, V. S. Rana, H. Sood, and M. Nandal, “Sustainable effect of polycarboxylate ether based admixture: A meticulous experiment to hardened concrete,” Mater Today Proc, (2022). [Google Scholar]
- M. Nandal, H. Sood, P. K. Gupta, and M. Z. U. Haq, “Morphological and physical characterization of construction and demolition waste,” Mater Today Proc, (2022). [Google Scholar]
- S. Kumar, A. Chopra, and M. Z. U. Haq, “EXPERIMENTAL INVESTIGATION ON MARBLE DUST, RICE HUSK ASH, AND FLY ASH BASED GEOPOLYMER BRICK”. [Google Scholar]
- V. S. Rana et al., “Assortment of latent heat storage materials using multi criterion decision making techniques in Scheffler solar reflector,” International Journal on Interactive Design and Manufacturing (IJIDeM), pp. 1–15, (2023). [Google Scholar]
- A. Saini, G. Singh, S. Mehta, H. Singh, and S. Dixit, “A review on mechanical behaviour of electrodeposited Ni-composite coatings,” International Journal on Interactive Design and Manufacturing, (2022). doi: 10.1007/S12008-022-00969-Z. [Google Scholar]
- R. Shanmugavel et al., “Al-Mg-MoS2 Reinforced Metal Matrix Composites: Machinability Characteristics,” Materials, vol. 15, no. 13, Jul. (2022). doi: 10.3390/MA15134548. [CrossRef] [PubMed] [Google Scholar]
- D. N. Nguyen, M. P. Dang, S. Dixit, and T. P. Dao, “A design approach of bonding head guiding platform for die to wafer hybrid bonding application using compliant mechanism,” International Journal on Interactive Design and Manufacturing, (2022). doi: 10.1007/S12008-022-01019-4. [Google Scholar]
- V. S. Rana et al., “Assortment of latent heat storage materials using multi criterion decision making techniques in Scheffler solar reflector,” International Journal on Interactive Design and Manufacturing, (2023). doi: 10.1007/S12008-023-01456-9. [Google Scholar]
- J. Singh et al., “Computational parametric investigation of solar air heater with dimple roughness in S-shaped pattern,” International Journal on Interactive Design and Manufacturing, (2023). doi: 10.1007/S12008-02301392-8. [Google Scholar]
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